Fuzzy multiple objective optimal system design by hybrid genetic algorithm |
| |
| Affiliation: | 1. State Key Laboratory of Pharmaceutical Biotechnology, Nanjing University, Nanjing 210023, People’s Republic of China;2. College of Chemical Engineering, Nanjing Forestry University, Nanjing 210073, People’s Republic of China;1. Fundação Getulio Vargas (FGV), Escola de Administração de Empresas de São Paulo (EAESP), Departamento de Tecnologia e Ciência de Dados (Technology & Data Science – TDS), Rua Itapeva 474 – 9 Andar, Sala 901, Bairro Bela Vista, São Paulo, 01332-000, SP, Brazil;2. University of Ljubljana, Faculty of Social Sciences, Kardeljeva Pl. 5, 1000, Ljubljana, Slovenia |
| |
| Abstract: | In this paper, we propose a method for solving fuzzy multiple objective optimal system design problems with GUB structure by hybridized genetic algorithms (HGA). This approach enables the flexible optimal system design by applying fuzzy goals and fuzzy constraints. In this genetic algorithm (GA), we propose the new chromosomes representation that represents the GUB structure simply and effectively at the same time. Also, by introducing the HGA that combine the proposed heuristic algorithm that makes use of the peculiarity of GUB structure to GA, the proposed approach is efficient than the previous method in finding solution. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
